class_docstr: This class is used for GPLVM models to recover a MAP estimate of
  the latent variable :math:`\mathbf X`, based on some supplied prior.
  
  :param int n: Size of the latent space.
  :param int latent_dim: Dimensionality of latent space.
  :param torch.Tensor X_init: initialization for the point estimate of :math:`\mathbf X`
  :param ~gpytorch.priors.Prior prior_x: prior for :math:`\mathbf X`
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code: def __init__(self, n, latent_dim, X_init, prior_x):
      super().__init__(n, latent_dim)
      self.prior_x = prior_x
      self.register_parameter("X", X_init)
      self.register_prior("prior_x", prior_x, "X")
  
file_path: gpytorch/gpytorch/models/gplvm/latent_variable.py
imports: import torch
  from ...module import Module
label_desc: Use image node_id 1 to create a new MAPLatentVariable object from inherited base classes: LatentVariable with example: obj = MAPLatentVariable(n, latent_dim, X_init, prior_x)